Dr Tao Geng
| Name | Dr Tao Geng |
|---|---|
| Job title | Lecturer in Design Engineering |
| Research institute | |
| Primary appointment | Design Engineering & Mathematics |
| ORCID | https://orcid.org/0000-0002-6863-243X |
| Contact category | Academic staff (past) |
Research outputs
The effect of swing leg retraction on biped walking stability is influenced by the walking speed and step-length
Bao, R. and Geng, T. 2018. The effect of swing leg retraction on biped walking stability is influenced by the walking speed and step-length. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain 01 - 05 Oct 2018 IEEE. pp. 3257-3262 https://doi.org/10.1109/IROS.2018.8593932Fast walking with rhythmic sway of torso in a 2D passive ankle walker
Bao, R. and Geng, T. 2018. Fast walking with rhythmic sway of torso in a 2D passive ankle walker. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain 01 - 05 Oct 2018 IEEE. pp. 4363-4368 https://doi.org/10.1109/IROS.2018.8593665Wrist movement detector for ROS based control of the robotic hand
Krawczyk, M., Yang, Z., Gandhi, V., Karamanoglu, M., Franca, F., Priscila, L., Xiaochen, W. and Geng, T. 2018. Wrist movement detector for ROS based control of the robotic hand. Advances in Robotics & Automation. 7 (1). https://doi.org/10.4172/2168-9695.1000182Using robot operating system (ROS) and single board computer to control bioloid robot motion
Kalyani, G., Yang, Z., Gandhi, V. and Geng, T. 2017. Using robot operating system (ROS) and single board computer to control bioloid robot motion. 18th Towards Autonomous Robotic Systems (TAROS) Conference. Guildford, Surrey, UK 19 - 21 Jul 2017 Springer. pp. 41-50 https://doi.org/10.1007/978-3-319-64107-2_4ROS based autonomous control of a humanoid robot
Kalyani, G., Gandhi, V., Yang, Z. and Geng, T. 2016. ROS based autonomous control of a humanoid robot. 25th International Conference on Artificial Neural Networks (ICANN). Barcelona, Spain 06 - 09 Sep 2016 Springer. pp. 550-551 https://doi.org/10.1007/978-3-319-44778-0Skins and sleeves for soft robotics: inspiration from nature and architecture
Lekakou, C., Elsayed, Y., Geng, T. and Saaj, C. 2015. Skins and sleeves for soft robotics: inspiration from nature and architecture. Advanced Engineering Materials. 17 (8), pp. 1180-1188. https://doi.org/10.1002/adem.201400406A unified system identification approach for a class of pneumatically-driven soft actuators
Wang, X., Geng, T., Elsayed, Y., Saaj, C. and Lekakou, C. 2015. A unified system identification approach for a class of pneumatically-driven soft actuators. Robotics and Autonomous Systems. 63, pp. 136-149. https://doi.org/10.1016/j.robot.2014.08.017Finite element analysis and design optimization of a pneumatically actuating silicone module for robotic surgery applications
Elsayed, Y., Vincensi, A., Lekakou, C., Geng, T., Saaj, C., Ranzani, T., Cianchetti, M. and Menciassi, A. 2014. Finite element analysis and design optimization of a pneumatically actuating silicone module for robotic surgery applications. Soft Robotics. 1 (4), pp. 255-262. https://doi.org/10.1089/soro.2014.0016Torso inclination enables faster walking in a planar biped robot with passive ankles
Geng, T. 2014. Torso inclination enables faster walking in a planar biped robot with passive ankles. IEEE Transactions on Robotics. 30 (3), pp. 753-758. https://doi.org/10.1109/TRO.2014.2298058Online regulation of the walking speed of a planar limit cycle walker via model predictive control
Geng, T. 2014. Online regulation of the walking speed of a planar limit cycle walker via model predictive control. IEEE Transactions on Industrial Electronics. 61 (5), pp. 2326-2333. https://doi.org/10.1109/TIE.2013.2272274Synergy-based affordance learning for robotic grasping
Geng, T., Wilson, J., Sheldon, M., Lee, M. and Hülse, M. 2013. Synergy-based affordance learning for robotic grasping. Robotics and Autonomous Systems. 61 (12), pp. 1626-1640. https://doi.org/10.1016/j.robot.2013.07.002Transferring human grasping synergies to a robot
Geng, T., Lee, M. and Hülse, M. 2011. Transferring human grasping synergies to a robot. Mechatronics. 21 (1), pp. 272-284. https://doi.org/10.1016/j.mechatronics.2010.11.003A self-paced online BCI for mobile robot control
Geng, T., Gan, J. and Hu, H. 2010. A self-paced online BCI for mobile robot control. International Journal of Advanced Mechatronic Systems. 2 (1/2), p. 28. https://doi.org/10.1504/IJAMECHS.2010.030846Planar biped walking with an equilibrium point controller and state machines
Geng, T. and Gan, J. 2010. Planar biped walking with an equilibrium point controller and state machines. IEEE/ASME transactions on mechatronics. 15 (2), pp. 253-260. https://doi.org/10.1109/TMECH.2009.2024742A novel design of 4-class BCI using two binary classifiers and parallel mental tasks
Geng, T., Gan, J., Dyson, M., Tsui, C. and Sepulveda, F. 2008. A novel design of 4-class BCI using two binary classifiers and parallel mental tasks. Computational Intelligence and Neuroscience. 2008, pp. 1-5. https://doi.org/10.1155/2008/437306Adaptive, fast walking in a biped robot under neuronal control and learning
Manoonpong, P., Geng, T., Kulvicius, T., Porr, B. and Wörgötter, F. 2007. Adaptive, fast walking in a biped robot under neuronal control and learning. PLoS Computational Biology. 3 (7), p. e134. https://doi.org/10.1371/journal.pcbi.0030134A reflexive neural network for dynamic biped walking control
Geng, T., Porr, B. and Wörgötter, F. 2006. A reflexive neural network for dynamic biped walking control. Neural Computation. 18 (5), pp. 1156-1196. https://doi.org/10.1162/089976606776241057Fast biped walking with a sensor-driven neuronal controller and real-time online learning
Geng, T. 2006. Fast biped walking with a sensor-driven neuronal controller and real-time online learning. The International Journal of Robotics Research. 25 (3), pp. 243-259. https://doi.org/10.1177/0278364906063822Dynamics and trajectory planning of a planar flipping robot
Geng, T. 2005. Dynamics and trajectory planning of a planar flipping robot. Mechanics Research Communications. 32 (6), pp. 636-644. https://doi.org/10.1016/j.mechrescom.2004.06.009984
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